dminiotas05 commited on
Commit
360fb18
·
1 Parent(s): 8726a28

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +63 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: distilbert-base-uncased-finetuned-ft1500_norm300_aug5_10_8x_plus_8_10_4x
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # distilbert-base-uncased-finetuned-ft1500_norm300_aug5_10_8x_plus_8_10_4x
16
+
17
+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.0732
20
+ - Mse: 4.2926
21
+ - Mae: 1.3756
22
+ - R2: 0.4728
23
+ - Accuracy: 0.3427
24
+
25
+ ## Model description
26
+
27
+ More information needed
28
+
29
+ ## Intended uses & limitations
30
+
31
+ More information needed
32
+
33
+ ## Training and evaluation data
34
+
35
+ More information needed
36
+
37
+ ## Training procedure
38
+
39
+ ### Training hyperparameters
40
+
41
+ The following hyperparameters were used during training:
42
+ - learning_rate: 2e-05
43
+ - train_batch_size: 4
44
+ - eval_batch_size: 4
45
+ - seed: 42
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - num_epochs: 2
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
53
+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
54
+ | 0.7013 | 1.0 | 7652 | 1.0583 | 4.2330 | 1.5178 | 0.4801 | 0.2056 |
55
+ | 0.3648 | 2.0 | 15304 | 1.0732 | 4.2926 | 1.3756 | 0.4728 | 0.3427 |
56
+
57
+
58
+ ### Framework versions
59
+
60
+ - Transformers 4.21.1
61
+ - Pytorch 1.12.1+cu113
62
+ - Datasets 2.4.0
63
+ - Tokenizers 0.12.1